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A comparison of a gradient boosting decision tree, random forests, and artificial neural networks to model urban land use changes: the case of the Seoul metropolitan area / Myung-Jin Jun in International journal of geographical information science IJGIS, vol 35 n° 11 (November 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 11 (November 2021) . - pp 2149 - 2167 Titre : A comparison of a gradient boosting decision tree, random forests, and artificial neural networks to model urban land use changes: the case of the Seoul metropolitan area Type de document : Article/Communication Auteurs : Myung-Jin Jun, Auteur Année de publication : 2021 Article en page(s) : pp 2149 - 2167 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse comparative [Termes IGN] arbre de décision [Termes IGN] changement d'utilisation du sol [Termes IGN] classification par forêts aléatoires [Termes IGN] Extreme Gradient Machine [Termes IGN] modèle de simulation [Termes IGN] réseau neuronal artificiel [Termes IGN] Séoul [Termes IGN] zone urbaine Résumé : (auteur) This study compares the performance of gradient boosting decision tree (GBDT), artificial neural networks (ANNs), and random forests (RF) methods in LUC modeling in the Seoul metropolitan area. The results of this study showed that GBDT and RF have higher predictive power than ANN, indicating that tree-based ensemble methods are an effective technique for LUC prediction. Along with the outstanding predictive performance, the DT-based ensemble models provide insights for understanding which factors drive LUCs in complex urban dynamics with the relative importance and nonlinear marginal effects of predictor variables. The GBDT results indicate that distance to the existing residential site has the highest contribution to urban land use conversion (30.4% of the relative importance), while other significant predictor variables were proximity to industrial and public sites (combined 32.3% of relative importance). New residential development is likely to be adjacent to existing residential sites, but nonresidential development occurs at a distance (about 600 m) from such sites. The distance to the central business district (CBD) had increasing marginal effects on residential land use conversion, while no significant pattern was found for nonresidential land use conversion, indicating that Seoul has experienced more population suburbanization than employment decentralization. Numéro de notice : A2021-756 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.1887490 Date de publication en ligne : 01/03/2021 En ligne : https://doi.org/10.1080/13658816.2021.1887490 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98771 [article]

A spatial model of cognitive distance in cities / Ed Manley in International journal of geographical information science IJGIS, vol 35 n° 11 (November 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 11 (November 2021) . - pp 2316 - 2338 Titre : A spatial model of cognitive distance in cities Type de document : Article/Communication Auteurs : Ed Manley, Auteur ; Gabriele Filomena, Auteur ; Panos Mavros, Auteur Année de publication : 2021 Article en page(s) : pp 2316 - 2338 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] cognition [Termes IGN] distance [Termes IGN] espace euclidien [Termes IGN] espace urbain [Termes IGN] modélisation spatiale [Termes IGN] morphologie urbaine [Termes IGN] perception [Termes IGN] positionnement statique [Termes IGN] représentation mentale spatiale [Termes IGN] système d'information urbain Résumé : (auteur) Spatial cognition is fundamental to the behaviour and activity of humans in urban space. Humans perceive their environments with systematic biases and errors, and act upon these perceptions, which in turn form urban patterns of activity. These perceptions are influenced by a multitude of factors, many of them relating to the static urban form. Yet much of geographic analysis ignores the influence of urban form, instead referring most commonly to the Euclidean arrangement of space. In this paper, we propose a novel spatial modelling framework for estimating cognitive distance in urban space. This framework is constructed from a wealth of research describing the effect of environmental factors on distance estimation, and produces a quantitative estimate of the effect based on standard GIS data. Unlike other cost measures, the cognitive distance estimate integrates systematically observed distortions and biases in spatial cognition. As a proof-of-concept, the framework is implemented for 26 cities worldwide using open data, producing a novel comparative measure of ‘cognitive accessibility’. The paper concludes with a discussion of the potential of this approach in analysing and modelling urban systems, and outlines areas for further research. Numéro de notice : A2021-761 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.1887488 Date de publication en ligne : 19/02/2021 En ligne : https://doi.org/10.1080/13658816.2021.1887488 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98790 [article]

Urban land-use analysis using proximate sensing imagery: a survey / Zhinan Qiao in International journal of geographical information science IJGIS, vol 35 n° 11 (November 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 11 (November 2021) . - pp 2129 - 2148 Titre : Urban land-use analysis using proximate sensing imagery: a survey Type de document : Article/Communication Auteurs : Zhinan Qiao, Auteur ; Xiaohui Yuan, Auteur Année de publication : 2021 Article en page(s) : pp 2129 - 2148 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] détection d'objet [Termes IGN] données issues des réseaux sociaux [Termes IGN] données localisées des bénévoles [Termes IGN] image Streetview [Termes IGN] utilisation du sol [Termes IGN] zone urbaine Résumé : (auteur) Urban regions are complicated functional systems that are closely associated with and reshaped by human activities. The propagation of online geographic information-sharing platforms and mobile devices equipped with the Global Positioning System (GPS) greatly proliferates proximate sensing images taken near or on the ground at a close distance to urban targets. Studies leveraging proximate sensing images have demonstrated great potential to address the need for local data in the urban land-use analysis. This paper reviews and summarizes the state-of-the-art methods and publicly available data sets from proximate sensing to support land-use analysis. We identify several research problems in the perspective of examples to support the training of models and means of integrating diverse data sets. Our discussions highlight the challenges, strategies, and opportunities faced by the existing methods using proximate sensing images in urban land-use studies. Numéro de notice : A2021-759 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.1919682 Date de publication en ligne : 03/05/2021 En ligne : https://doi.org/10.1080/13658816.2021.1919682 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98788 [article]

Predicting total electron content in ionosphere using vector autoregression model during geomagnetic storm / Sumitra Iyer in Journal of applied geodesy, vol 15 n° 4 (October 2021)  

Public [article]  inJournal of applied geodesy > vol 15 n° 4 (October 2021) . - pp 279 - 291 Titre : Predicting total electron content in ionosphere using vector autoregression model during geomagnetic storm Type de document : Article/Communication Auteurs : Sumitra Iyer, Auteur ; Alka Mahajan, Auteur Année de publication : 2021 Article en page(s) : pp 279 - 291 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes IGN] autorégression [Termes IGN] déformation temporelle dynamique [Termes IGN] format RINEX [Termes IGN] Inde [Termes IGN] modèle de simulation [Termes IGN] modèle ionosphérique [Termes IGN] série temporelle [Termes IGN] signal GPS [Termes IGN] tempête magnétique [Termes IGN] teneur totale en électrons [Termes IGN] teneur verticale totale en électrons Résumé : (auteur) The ionospheric total electron content (TEC) severely impacts the positional accuracy of a single frequency Global Positioning System (GPS) receiver at the equatorial latitudes. The ionosphere causes a frequency-dependent group delay in the GPS-ranging signals, which reduces the receiver’s accuracy. Further, the variations in TEC due to various space weather phenomena make the ionosphere’s behaviour nonhomogeneous and complex. Hence, developing an accurate forecast model that can track the dynamic behaviour of the ionosphere remains a challenge. However, advances in emerging data-driven algorithms have been found helpful in tracking non-stationary behavior in TEC. These models help forecast the delays in advance. The multivariate Vector Autoregression model (VAR) predicts the Ionospheric TEC in the proposed model. The prediction model uses input data compiled in real-time from the lag values of incoming TEC data and features extracted from TEC. The TEC is predicted in real-time and tested for different prediction intervals. The metrics – Mean Percentage Error (MAPE), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) are used for testing and validating the accuracy of the model statistically. Testing the predicted output accuracy is also done with the dynamic time warping (DTW) algorithm by comparing it with the actual value obtained from the dual-frequency receiver. The model is tested for storm days of the year 2015 for Bangalore and Hyderabad stations and found to be reliable and accurate. A prediction interval of twenty-minute shows the highest accuracy with an error within 10 TECU for all the storm days. Numéro de notice : A2021-749 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1515/jag-2021-0015 Date de publication en ligne : 23/06/2021 En ligne : https://doi.org/10.1515/jag-2021-0015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98717 [article]

Evaluating urban intensity through a city information model - intermediate results from an action research project / Adeline Deprêtre in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol VIII-4/W2-2021 ([07/10/2021])  

Public [article]  inISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol VIII-4/W2-2021 [07/10/2021] . - pp 153 - 160 Titre : Evaluating urban intensity through a city information model - intermediate results from an action research project Type de document : Article/Communication Auteurs : Adeline Deprêtre, Auteur ; Florence Jacquinod , Auteur Année de publication : 2021 Projets : 1-Pas de projet / Conférence : 3D GeoInfo 2021, 16th 3D GeoInfo conference 11/10/2021 14/10/2021 New York City New-York - Etats-Unis OA ISPRS Annals Article en page(s) : pp 153 - 160 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] espace public [Termes IGN] indicateur [Termes IGN] modèle 3D de l'espace urbain [Termes IGN] modélisation 3D du bâti BIM [Termes IGN] planification urbaine Résumé : (auteur) Urban planning is a very complex task, especially considering the many challenges it faces, including an increasing need for housing in response to demographic growth and a need to limit abusive land artificialisation. As part of an interdisciplinary action-research project focused on experimenting with various uses of an existing City Information Model (CIM) for urban design, we are developing a new indicator to characterize urban intensity and a method to quantify it through the City Information Model (CIM) of a French eco-district. Our project is ongoing, and, in this paper, we present intermediate results on the potential of this CIM to support the automated quantification of our urban intensity indicator. We also describe the solutions currently implemented so that our experimental CIM can provide the necessary information for a more complete and automated urban intensity analysis. Finally, we shed light on key issues regarding the use of CIM, specifically CIM made up of various BIM models (of buildings lots and public spaces) for urban analysis at the district scale during the design phase. These issues include the need to generalize BIM entities and to manage property sets and nomenclatures to allow automation of analyses at the district scale, as long as there is no BIM+ data model allowing for urban analysis. Numéro de notice : A2021-739 Affiliation des auteurs : UGE-LaSTIG+Ext (2020- ) Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprs-annals-VIII-4-W2-2021-153-2021 En ligne : https://doi.org/10.5194/isprs-annals-VIII-4-W2-2021-153-2021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98753 [article]

Impact of travel time uncertainties on modeling of spatial accessibility: a comparison of street data sources / Yan Lin in Cartography and Geographic Information Science, vol 48 n° 6 (October 2021)  

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Spatio-temporal-spectral observation model for urban remote sensing / Zhenfeng Shao in Geo-spatial Information Science, vol 24 n° 3 (October 2021)  

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The accuracy of urban maps in Spain through GIS: The example of Burgos from the nineteenth to the twentieth century / Barbara Polo-Martin in Cartographica, vol 56 n° 3 (Fall 2021)  

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Assessment and prediction of urban growth for a mega-city using CA-Markov model / Veerendra Yadav in Geocarto international, Vol 36 n° 17 ([21/09/2021])  

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On the suitability of a unified GIS-BIM-HBIM framework for cataloguing and assessing vulnerability in Historic Urban Landscapes: a critical review / Rafael Ramirez Eudave in International journal of geographical information science IJGIS, vol 35 n° 10 (October 2021)  

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Access to urban parks: Comparing spatial accessibility measures using three GIS-based approaches / Siqin Wang in Computers, Environment and Urban Systems, vol 90 (November 2021)  

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Analytics of location-based big data for smart cities: Opportunities, challenges, and future directions / Haosheng Huang in Computers, Environment and Urban Systems, vol 90 (November 2021)  

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Calibration of cellular automata urban growth models from urban genesis onwards - a novel application of Markov chain Monte Carlo approximate Bayesian computation / Jingyan Yu in Computers, Environment and Urban Systems, vol 90 (November 2021)  

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Double adaptive intensity-threshold method for uneven Lidar data to extract road markings / Chengming Ye in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 9 (September 2021)  

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A framework for ecosystem service assessment using GIS interoperability standards / Martin Lacayo in Computers & geosciences, vol 154 (September 2021)  

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